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基于软计算技术的军用软件可靠性预测模型研究 被引量:1

Research on Military Software Reliability Prediction Model Based on Soft Computing Technology
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摘要 针对软件可靠性预测模型不能适用于现实环境中所有情况的问题,设计一种基于软计算技术的军用软件可靠性预测模型。通过分析使用软计算技术解决军用软件可靠性预测的前景,在介绍软件可靠性概念的基础上,对软件可靠性预测模型进行分类,讨论了使用软计算技术预测军用软件可靠性的不同方法,对军用软件可靠性预测的度量标准和失效的预测方法的评估指标开展研究,比较了通用的软件失效数据集的来源、特点和缺陷数目,总结了常用的可靠性预测工具的特点和适用范围。分析结果表明:采用软计算技术解决军用软件可靠性预测问题,能够优化测试效果,符合军用软件的实际情况。 For software reliability prediction model may not apply to all situations in real environment, a kind of military software reliability prediction model based on soft computing techniques are designed. By analyzing the use of soft computing technologies to solve the prospect of the military software reliability prediction, based on introducing the concept of software reliability, software reliability prediction model are classified, different methods about using of soft computing techniques to predict the reliability of military software are discusses, the military software reliability prediction of metrics and failure prediction method of evaluation are researched, a comprehensive list of some widely used failure datasets together with description, characteristic and number of failures are compared, the characteristic and application of the tools for software reliability modeling are summarized. Interrelated analyses conclude that using soft computing technology solve the problem of the military software reliability prediction, optimize the test result, in accordance with the actual situation of military software.
作者 孙媛 赵建军 周源 Sun Yuan Zhao Jianjun Zhou Yuan(Department of Scientific Research, Naval Aeronautical Engineering Institute, Yantai 26400 l, China Department of Armament Science & Technology, Naval Aeronautical Engineering Institute, Yantai 264001, China Department of Strategic Missile Engineering, Naval Aeronautical Engineering Institute, Yantai 26400l, China)
出处 《兵工自动化》 2017年第2期56-60,65,共6页 Ordnance Industry Automation
基金 全军军事类研究生资助课题(2015JY396)
关键词 软件可靠性 度量 预测工具 软计算 software reliability measure prediction tool soft computing
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